# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an &quot;AS IS&quot; BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


# NOTE: This class is auto generated by the swagger code generator program.
# https://github.com/swagger-api/swagger-codegen.git
# Do not edit the class manually.

defmodule GoogleApi.Prediction.V16.Model.Insert2ModelInfo do
  @moduledoc """
  Model metadata.

  ## Attributes

  - classWeightedAccuracy (String): Estimated accuracy of model taking utility weights into account (Categorical models only). Defaults to: `null`.
  - classificationAccuracy (String): A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an estimate, based on the amount and quality of the training data, of the estimated prediction accuracy. You can use this is a guide to decide whether the results are accurate enough for your needs. This estimate will be more reliable if your real input data is similar to your training data (Categorical models only). Defaults to: `null`.
  - meanSquaredError (String): An estimated mean squared error. The can be used to measure the quality of the predicted model (Regression models only). Defaults to: `null`.
  - modelType (String): Type of predictive model (CLASSIFICATION or REGRESSION). Defaults to: `null`.
  - numberInstances (String): Number of valid data instances used in the trained model. Defaults to: `null`.
  - numberLabels (String): Number of class labels in the trained model (Categorical models only). Defaults to: `null`.
  """

  defstruct [
    :"classWeightedAccuracy",
    :"classificationAccuracy",
    :"meanSquaredError",
    :"modelType",
    :"numberInstances",
    :"numberLabels"
  ]
end

defimpl Poison.Decoder, for: GoogleApi.Prediction.V16.Model.Insert2ModelInfo do
  def decode(value, _options) do
    value
  end
end

defimpl Poison.Encoder, for: GoogleApi.Prediction.V16.Model.Insert2ModelInfo do
  def encode(value, options) do
    GoogleApi.Prediction.V16.Deserializer.serialize_non_nil(value, options)
  end
end

